A hybrid genetic algorithm and bacterial foraging approach for global optimization
By Dong Hwa Kim, Ajith Abraham, Jae-Hoon Cho. Information Sciences, 2007
522 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/772f83c311649ad3ca2baf1c7c4de4610315a077
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Andreas Holzinger
- Seyedali Mirjalili
- Vasile Palade
- Katharina Holzinger
- Tansel Dökeroğlu
- Raul Rabadan
- Ajith Abraham
- Swagatam Das
In Molecular Biology
- Sidhartha Panda
- Binod Kumar Sahu
- Pradeep Kumar Mohanty
- Ajith Abraham
- Vasile Palade
- Ahmet Cosar
- Tansel Dökeroğlu
- Swagatam Das
Citations in the corpus
- Darwin or Lamarck? Future Challenges in Evolutionary Algorithms for Knowledge Discovery and Data Mining (2014, background): “coli can be used by analogy in the Bacteria Foraging Algorithms (BFA) to solve global optimization problems [69].”
- IMPROVED ADAPTIVE BACTERIA FORAGING ALGORITHM IN OPTIMIZATION OF ANTENNA ARRAY FOR FASTER CONVERGENCE (2008, unknown): “In [29], proposed a hybrid approach involving GA and BFA to tune PID controller (proportional-integral-derivative controller) of an automatic voltage regulator and has shown the efficiency of this approach for global optimization problems.”
- Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications (2009, methodology): “proposed a hybrid approach involving genetic algorithm (GA) and BFOA for function optimization [19].”
- A survey on new generation metaheuristic algorithms (2019, methodology): “Mirjalili (2016a) proposes swarm intelligence optimization technique Dragonfly Algorithm (KS and Murugan, 2017). Karaboga (2005) presents a report on the swarms of Honey Bees to optimize the combinatorial problems.”
- Tuning and Assessment of Proportional–Integral–Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm (2014, methodology): “[12] proposed a hybrid approach involving the GA and bacterial foraging optimization algorithms (BFOAs) to tune a PID controller of an AVR system.”
- GSA: A Gravitational Search Algorithm (2009, background): “…biological immune systems [8], Ant Colony Optimization, ACO, mimics the behavior of ants foraging for food [5], Bacterial Foraging Algorithm, BFA, comes from search and optimal foraging of bacteria [11,19] and Particle Swarm Optimization, PSO, simulates the behavior of flock of birds [3,17].”